Abstract
This study evaluates physical activity in patients with advanced hip OA using Fitbit and whether a correlation exists between the number of steps taken per day (SPD) and the reported outcome.
Methods
122 patients were prospective enrolled. Patient-reported outcomes were collected. Patients were asked to wear a Fitbit for 24 h a day on seven consecutive days.
Result
The mean number of SPD was 5721 ± 3920. The UCLA, HHS and SF-12 PCS demonstrated a statistically significant positive correlation with the SPD.
Conclusion
Wearable technology is reliable in objectively measuring the level of physical activity in hip OA and correlates with reported outcomes.
Keywords: Total hip arthroplasty, Self-reported physical activity, WOMAC, Fitbit, Wearable technology
1. Introduction
Osteoarthritis (OA) is a degenerative disease that causes progressive loss of the articular cartilage leading to permanent joint destruction.1 The incidence of OA is 10.9% in the general population with an expected significant increase in the future as a result of the rise in the aging population.2 OA leads to debilitating joint pain and restricted range of motion that results into decline in patient's functional capacity and quality of life.
Level of physical activity is an important variable affecting one's quality of life and it includes the ability to walk, work, performing house-hold chores and any recreational activities.3 Different tools have been developed to assess patient's physical activity in clinical and research settings. These tools include activity scales, questionnaires and wearable technologies.4 Activity scales and questionnaires are easily available but are subjective and tend to overestimate the level of physical activity by patients.5,6 On the other hand, wearable technology is an objective and accurate method to assess physical activity. Wearable technology works by measuring the number of steps walked then by using of an algorithm it estimates walked distances, intensity of activity performed and burned calories.7,8 This technology has been validated in multiple studies.9, 10, 11
Despite their accuracy, the use of wearable technology as a measurement tool of physical activity in daily clinical practice is limited. Therefore, it is important to establish whether commonly used patient-reported outcome scores correlate with objective measures of activity to identify outcome scores that can accurately reflect patient's activity levels. There have been limited studies that have validated commonly used patient-reported outcome scores against objective measures of physical activity such as wearable technology.12,13 To our knowledge, the University of California Los Angeles (UCLA) activity scale,14 36-Item Short Form Survey (SF-36),15 8-Item Short Form Survey (SF-8)16 and the Harris Hip Score (HHS)17 has been correlated to physical activity levels objectively measured by wearable technology where others such as Western Ontario and McMaster Universities Arthritis Index (WOMAC)18 and 12-Item Short Form Survey (SF-12)19 have yet to be studied against objective measures.
The purpose of this study is to 1) objectively evaluate physical activity in patients with end-stage hip OA using a wristband activity tracker, 2) to correlate the number of steps taken to a patient-reported physical activity scale, UCLA, as well as other patient-reported outcome scores; specifically the WOMAC, the PCS of the SF-12 and HHS and 3) to explore the effect of age, body mass index (BMI), and medical co-morbidities measured by the Charlson Co-morbidity Score (CCS) on the mean number of steps taken per day.
2. Materials and methods
This was a prospective study that was performed between September 2015 and March 2016 at our institution. Institutional Review Board approval was obtained before the onset of the study. Inclusion criteria were patients with hip OA who failed non-operative treatment and in whom a primary total hip arthroplasty (THA) was indicated. Exclusion criteria included patients with inflammatory hip arthritis, prior hip surgery, prior infection, contralateral hip pathology that would affect activity, and patients not willing to participate in the study.
Demographics such as, height, weight, age, and medical co-morbidities were collected. The number of steps was recorded using a validated wristband activity tracker, Fitbit® Flex (Fitbit Inc., San Francisco, CA, USA).20 All patients were asked to wear the wristband for 24 h a day, except for water activities, on seven consecutive days within the four weeks preceding their scheduled THA. Patients were given instruction on how to operate the wristband and wear it, along with a detailed instruction sheet. All patients were also given an information sheet to document the times and reasons they took the wristband off. Data was downloaded as number of steps taken per day. The UCLA,14 WOMAC, PCS SF-12 and HHS were obtained during the same time period.
Demographics, number of steps taken and patient-reported outcome scores were reported with descriptive statistics including means, standard deviations and ranges. To determine whether a relationship exists between the number of steps taken and patient-reported outcome scores as well as age, BMI and CCS, correlational analysis with Spearman correlation coefficient (rho) was performed. To determine the effect of demographics on activity levels, patient cohorts were categorized by age, gender and BMI. The mean number of steps was compared in patients older than 65 years old to patients aged 65 or younger, male to females, and in patients with BMI ≤30 kg/m2 compared to patients with BMI >30 kg/m2 with a Mann-Whitney U test. SPSS® v.22 (SPSS Inc., Chicago, IL, USA) was used for all analyses. Statistical significance was set at p < 0.05.
3. Results
One hundred and twenty-two patients were identified to fit the inclusion criteria and were included in the study. There were 51 males and 71 females. The mean age was 65 years (range 32–89 years), the mean BMI was 30.1 kg/m2 (range 20.1–87.1 kg/m2), and the mean CCS was 2.5 (range 0–8). The mean number of steps taken per day was 5721 ± 3920 (range 655–21223 steps/day). All other outcomes fell within an expected range of a patient with end-stage hip arthritis (Table 1).
Table 1.
Descriptive data of steps per day and other patient-reported outcome scores.
| Mean ± SD | Range | |
|---|---|---|
| Steps per day | 5721 ± 3920 | 655–21223 |
| UCLA | 4.37 ± 1.8 | 1–10 |
| WOMAC | 45.7 ± 16.6 | 0–91 |
| PCS SF-12 | 31.6 ± 9.1 | 17.6–59 |
| HHS | 50.9 ± 13.3 | 23–76 |
UCLA=The University of California, Los Angeles activity score, HHS=Harris Hip Score, WOMAC = the Western Ontario and McMaster Universities Arthritis Index and PCS SF-12 = the Physical Component Summery of the 12- Item Short Form Survey.
All collected patient-reported outcome scores were correlated to the number of steps walked per day (Table 2). The UCLA scale, the HHS and PCS SF-12 demonstrated a statistically significant positive correlation with the number of steps per day with a Spearman correlation coefficient of rho = 0.39 (p = 0.0001), rho = 0.37 (p = 0.001) and rho = 0.31 (p = 0.005) respectively. The WOMAC score did not correlate well with the number of steps walked per day with a Spearman correlation coefficient of rho = 0.005 (p = 0.97).
Table 2.
Correlations between steps per day with other patient-reported outcome scores using the Spearman correlation coefficient value (rho).
| Steps/day | p-value | |
|---|---|---|
| UCLA | 0.393 | 0.0001 |
| HHS (Total) | 0.365 | 0.001 |
| SF 12 (PCS) | 0.305 | 0.005 |
| WOMAC (Total) | 0.005 | 0.965 |
UCLA=The University of California, Los Angeles activity score, HHS=Harris Hip Score, WOMAC = the Western Ontario and McMaster Universities Arthritis Index and PCS SF-12 = the Physical Component Summery of the 12-Item Short Form Survey.
Age, BMI and CCS were not found to correlate well with the numbers of steps walked per day with a Spearman Correlation coefficient of rho = −0.019 (p = 0.841), rho = −0.028 (p = 0.776) and rho = −0.107 (p = 0.276) respectively. (Table 3).
Table 3.
Correlations between steps per day with age, BMI and CCS using the Spearman correlation coefficient value (rho).
| Correlation Coefficient | p-value | |
|---|---|---|
| Age | −0.392 | 0.841 |
| BMI | −0.177 | 0.071 |
| CCS | −0.415 | 0.276 |
BMI= Body Mass Index, CCS= Charlson Co-morbidity score.
Even though age and BMI were not found to correlate well with the numbers of steps walked per day, we wanted to see if this might be different with subgroup analysis. Therefore, we looked at the mean number of steps in patients older than 65 years old compared to patients aged 65 or younger, male to females, and in patients with BMI ≤30 kg/m2 compared to patients with BMI >30 kg/m2. The results showed that the mean number of steps walked per day in patients older than 65 years old was significantly lower than the mean number of steps for patients aged 65 or younger (p = 0.001). Similarly, there was significantly lower mean number of steps walked per day in patients with BMI >30 kg/m2 than the mean number of steps for patients with BMI <30 kg/m2 (p = 0.026). There was no significant difference in the mean number of steps in males compared to the mean number of steps in females (p = 0.22). (Table 4).
Table 4.
Comparing the mean steps per day in patients based on age, gender and BMI.
| Steps/day (mean ± SD) | p-value | |
|---|---|---|
| Total | 5720.887 ± 3920.056 | |
| Male Female |
6534.9 ± 4428.6 5466. ± 3645.2 |
0.22 |
| Age ≤65 Age >65 |
7111.8 ± 3937.4 4376.1 ± 3335.4 |
0.001 |
| BMI ≤30 kg/m2 BMI >30 kg/m2 |
6909 ± 4981.1 4822.8 ± 2756.6 |
0.026 |
BMI=Body Mass Index.
4. Discussion
The primary goal of this study was to evaluate the level of physical activity in patients with hip OA using wearable technology. The mean numbers of steps per day in this study was 5721 ± 3920 steps/day which is similar to other reported results in the literature. Holsgaard-Larsen A et al.21 compared the mean number of steps in 26 patients with end-stage hip OA to 15 healthy age-matched control patients. They reported that the mean numbers of steps in patients with OA was 6639 ± 3222 compared to 8576 ± 2872 in a healthy age-matched control group. Values lower than 5000 steps per day would classify the patient as sedentary based on the suggested criteria by Tudor-Lock.22,23 Based on this criteria 51% of the patients in this study would be considered sedentary. Harding et al.24 also, reported on the physical activity levels of 63 patients undergoing TKA or THA for end-stage OA using a waist accelerometer. They found that 82% of the patients were sedentary pre-operatively.
Moreover, all the patients with OA scored low on all patient-reported outcomes scores. This result is supported by recent literature.25,26 Boutron et al.25 evaluated disability and the quality of life in 1581 patients with end-stage hip OA in the primary-care setting. These patients reported a high level of disability with a mean WOMAC score of 45.2 ± 17.3 and decreased health-related quality of life with a mean PCS SF-36 score of 31.8 ± 8.4. Salaffi et al.26 also assessed the quality of life in 107 patients with end-stage hip OA using the WOMAC and the SF-36 scores and showed similar results.
The UCLA scale has been found to be the most valid patient-reported activity scale.8,17,25 In this study the UCLA scale demonstrated a significant positive correlation with the number of steps per day. Zhiri et al.,19 looked at the correlation between UCLA scale to the number of steps recorded by a pedometer and showed a strong positive correlation between the two variables. In addition, Alvarez et al.,17 showed a statistically significant positive correlation between the UCLA scale and physical activity measured by accelerometers using Spearman correlation coefficient (rho = 0.361, p = 0.015) in 47 patients following THA. Our findings and the presented literature support the validity of the UCLA scale as physical activity measurement tool. However, the UCLA scale is still a subjective patient-reported outcome score and can be limited by recall bias.
Although no studies correlated the 12-item short form survey against objectively measured physical activity in patients with OA, limited studies have examined other versions including the 8-item and 36-item short form survey. Fujita et al.27 showed no correlation between the 8-item short form survey and step counts in 38 female patients with end-stage hip OA awaiting an elective unilateral THA. On the other hand, Brandes et al.15 correlated the 36-item short form survey against number of steps in 26 patients with end-stage hip and knee OA. They found a positive correlation of physical functioning to step counts with a Pearson correlation coefficient (r) of 0.6 (p = 0.02). To our knowledge, this is the first study to show a positive correlation between objective measured physical activity (step count) and PCS SF 12 form. This has a significant clinical implication since it is shorter that the 36-item survey therefore, more convenient and easier to implement in daily clinical practice.
Another objective of this study was to explore the effect of age, BMI and medical co-morbidities on the number of steps taken per day. In this study, we found no correlation between BMI and the number of steps per day. This was in consensus with the results reported by Alvarez et al., in which they showed no correlation between physical activity levels measured by accelerometers and BMI.17 However, we did detect a difference in the mean number of steps in patients with BMI ≤30 kg/m2 compared to patients with BMI >30 kg/m2. It is well documented in the literature that physical inactivity can lead to obesity.28 However, few studies have assessed whether or not increased BMI could independently lead to physical inactivity and the effect of BMI on physical activity levels remains controversial.
Some of the limitations of this study include the lack of a control group. However, physical activity levels in a similar age-matched control group have been well documented in the current literature and can be compared to patients in our study. Another potential limitation is patient's compliance with wearing the activity tracker, especially older patients who are not familiar with using such a technology.
To our knowledge, this prospective cohort study is the first report to compare the WOMAC and SF-12 scores to step counts in patients with end-stage hip OA. Establishing such a correlation makes this report a valuable clinical study to a wide range of clinicians to help them assess physical activity levels in patients with end-stage OA.
5. Conclusion
In conclusion, physical activity level is an important dimension of quality of life and a critical prognostic factor following THA. Measurement of physical activity levels preoperatively can be used to predict functional recovering following THA. Wearable technology provides an accurate and reproducible measure of physical activity levels and has become more popular among the general population, making it a valuable tool for the healthcare providers to take advantage of it. This will allow a more accurate way of evaluating physical activity and will avoid the recall bias and activity overestimation that is associated with patient-reported questionnaires. However, in this study we were able to validate the use of UCLA activity scale as a simple alternative measurement tool of patient's physical activity levels.
Funding
This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.
Declaration of competing interest
All the Authors declare that they have no conflict of interest.
Contributor Information
Mina W. Morcos, Email: mina.wahbamorcos@mail.mcgill.ca.
Brent Lanting, Email: Brent.lanting@lhsc.on.ca.
References
- 1.Brown T.Q.C.M.W., Saleh K. first ed. 2009. The Hip. Philidelphia , PA. [Google Scholar]
- 2.Woolf A.D., Pfleger B. Burden of major musculoskeletal conditions. Bull World Health Organ. 2003;81(9):646–656. [PMC free article] [PubMed] [Google Scholar]
- 3.Brophy R.H., Lin K., Smith M.V. The role of activity level in orthopaedics: an important prognostic and outcome variable. J Am Acad Orthop Surg. 2014;22(7):430–436. doi: 10.5435/JAAOS-22-07-430. [DOI] [PubMed] [Google Scholar]
- 4.Terwee C.B., Bouwmeester W., van Elsland S.L., de Vet H.C., Dekker J. Instruments to assess physical activity in patients with osteoarthritis of the hip or knee: a systematic review of measurement properties. Osteoarthr Cartil. 2011;19(6):620–633. doi: 10.1016/j.joca.2011.01.002. [DOI] [PubMed] [Google Scholar]
- 5.de Groot I.B., Bussmann H.J., Stam H.J., Verhaar J.A. Small increase of actual physical activity 6 months after total hip or knee arthroplasty. Clin Orthop Relat Res. 2008;466(9):2201–2208. doi: 10.1007/s11999-008-0315-3. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.de Groot I.B., Bussmann J.B., Stam H.J., Verhaar J.A. Actual everyday physical activity in patients with end-stage hip or knee osteoarthritis compared with healthy controls. Osteoarthr Cartil. 2008;16(4):436–442. doi: 10.1016/j.joca.2007.08.010. [DOI] [PubMed] [Google Scholar]
- 7.El-Gayar O.T.P., Nawar N., Eid W. A systematic review of IT for diabetes self-management: are we there yet? Int J Med Inform. 2013;82(8):637–652. doi: 10.1016/j.ijmedinf.2013.05.006. [DOI] [PubMed] [Google Scholar]
- 8.Bravata D.M., Smith-Spangler C., Sundaram V. Using pedometers to increase physical activity and improve health: a systematic review. J Am Med Assoc. 2007;298(19):2296–2304. doi: 10.1001/jama.298.19.2296. [DOI] [PubMed] [Google Scholar]
- 9.Adam Noah J., Spierer D.K., Gu J., Bronner S. Comparison of steps and energy expenditure assessment in adults of Fitbit Tracker and Ultra to the Actical and indirect calorimetry. J Med Eng Technol. 2013;37(7):456–462. doi: 10.3109/03091902.2013.831135. [DOI] [PubMed] [Google Scholar]
- 10.Bassett D.R., Jr., Ainsworth B.E., Leggett S.R. Accuracy of five electronic pedometers for measuring distance walked. Med Sci Sport Exerc. 1996;28(8):1071–1077. doi: 10.1097/00005768-199608000-00019. [DOI] [PubMed] [Google Scholar]
- 11.Case M.A., Burwick H.A., Volpp K.G., Patel M.S. Accuracy of smartphone applications and wearable devices for tracking physical activity data. J Am Med Assoc. 2015;313(6):625–626. doi: 10.1001/jama.2014.17841. [DOI] [PubMed] [Google Scholar]
- 12.Alvarez A., Domenech J., Valverde-Mordt C., Lison J.F. Correlation between the level of physical activity as measured by accelerometer and the Harris Hip Score. Hip Int. 2015;25(5):461–465. doi: 10.5301/hipint.5000245. [DOI] [PubMed] [Google Scholar]
- 13.Morlock M., Schneider E., Bluhm A. Duration and frequency of every day activities in total hip patients. J Biomech. 2001;34(7):873–881. doi: 10.1016/s0021-9290(01)00035-5. [DOI] [PubMed] [Google Scholar]
- 14.Zahiri C.A.S.T., Szuszczewicz E.S., Amstutz H.C. Assessing activity in joint replacement patients. J Arthroplast. 1998;13(8):890–895. doi: 10.1016/s0883-5403(98)90195-4. [DOI] [PubMed] [Google Scholar]
- 15.Brandes M., Schomaker R., Mollenhoff G., Rosenbaum D. Quantity versus quality of gait and quality of life in patients with osteoarthritis. Gait Posture. 2008;28(1):74–79. doi: 10.1016/j.gaitpost.2007.10.004. [DOI] [PubMed] [Google Scholar]
- 16.Ware J.E., Jr., Bjorner J.B., Kosinski M. Practical implications of item response theory and computerized adaptive testing: a brief summary of ongoing studies of widely used headache impact scales. Med Care. 2000;38(9 Suppl):II73–82. [PubMed] [Google Scholar]
- 17.Harris W.H., Krushell R.J., Galante J.O. Results of cementless revisions of total hip arthroplasties using the Harris-Galante prosthesis. Clin Orthop Relat Res. 1988;(235):120–126. [PubMed] [Google Scholar]
- 18.Bellamy N., Buchanan W.W., Goldsmith C.H., Campbell J., Stitt L.W. Validation study of WOMAC: a health status instrument for measuring clinically important patient relevant outcomes to antirheumatic drug therapy in patients with osteoarthritis of the hip or knee. J Rheumatol. 1988;15(12):1833–1840. [PubMed] [Google Scholar]
- 19.Ware J., Jr., Kosinski M., Keller S.D. A 12-Item Short-Form Health Survey: construction of scales and preliminary tests of reliability and validity. Med Care. 1996;34(3):220–233. doi: 10.1097/00005650-199603000-00003. [DOI] [PubMed] [Google Scholar]
- 20.Evenson K.R., Goto M.M., Furberg R.D. Systematic review of the validity and reliability of consumer-wearable activity trackers. Int J Behav Nutr Phys Act. 2015;12(1):159. doi: 10.1186/s12966-015-0314-1. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Holsgaard-Larsen A., Roos E.M. Objectively measured physical activity in patients with end stage knee or hip osteoarthritis. Eur J Phys Rehabil Med. 2012;48(4):577–585. [PubMed] [Google Scholar]
- 22.Tudor-Locke C., Jones R., Myers A.M., Paterson D.H., Ecclestone N.A. Contribution of structured exercise class participation and informal walking for exercise to daily physical activity in community-dwelling older adults. Res Q Exerc Sport. 2002;73(3):350–356. doi: 10.1080/02701367.2002.10609031. [DOI] [PubMed] [Google Scholar]
- 23.Tudor-Locke C., Bassett D.R., Jr. How many steps/day are enough? Preliminary pedometer indices for public health. Sport Med. 2004;34(1):1–8. doi: 10.2165/00007256-200434010-00001. [DOI] [PubMed] [Google Scholar]
- 24.Harding P.H.A., Delany C., Hinman R.S. Do activity levels increase after total hip and knee arthroplasty? Clin Orthop Relat Res. 2014;472(5):1502–1511. doi: 10.1007/s11999-013-3427-3. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.Boutron I., Rannou F., Jardinaud-Lopez M., Meric G., Revel M., Poiraudeau S. Disability and quality of life of patients with knee or hip osteoarthritis in the primary care setting and factors associated with general practitioners' indication for prosthetic replacement within 1 year. Osteoarthr Cartil. 2008;16(9):1024–1031. doi: 10.1016/j.joca.2008.01.001. [DOI] [PubMed] [Google Scholar]
- 26.Salaffi F., Carotti M., Grassi W. Health-related quality of life in patients with hip or knee osteoarthritis: comparison of generic and disease-specific instruments. Clin Rheumatol. 2005;24(1):29–37. doi: 10.1007/s10067-004-0965-9. [DOI] [PubMed] [Google Scholar]
- 27.Fujita K., Makimoto K., Tanaka R., Mawatari M., Hotokebuchi T. Prospective study of physical activity and quality of life in Japanese women undergoing total hip arthroplasty. J Orthop Sci. 2013;18(1):45–53. doi: 10.1007/s00776-012-0318-5. [DOI] [PubMed] [Google Scholar]
- 28.Thasanasuwan W., Srichan W., Kijboonchoo K. Low sleeping time, high TV viewing time, and physical inactivity in school are risk factors for obesity in pre-adolescent Thai children. J Med Assoc Thail. 2016;99(3):314–321. [PubMed] [Google Scholar]